Developing symbols which have some value is a trait unique to humans. Recognizing these symbols and understanding the letters on an image is absolutely normal for us. We never really grasp letters like computers do, we completely base our ability to read them on our sight.
On the other
Transfer learning is a powerful technique for training deep neural networks that allows one to take knowledge learned about one deep learning problem and apply it to a different, yet similar learning problem.
Using transfer learning can dramatically speed up the rate of deployment for an app you are
This is the 17th article in my series of articles on Python for NLP. In the last article, we started our discussion about deep learning for natural language processing.
The previous article was focused primarily towards word embeddings, where we saw how the word embeddings can be used to convert
Genetic algorithms are a part of a family of algorithms for global optimization called Evolutionary Computation, which is comprised of artificial intelligence metaheuristics with randomization inspired by biology.
In the previous article, Introduction to Genetic Algorithms in Java, we've covered the terminology and theory behind all of the things
Genetic algorithms are a part of a family of algorithms for global optimization called Evolutionary Computation, which is comprised of artificial intelligence metaheuristics with randomization inspired by biology. Wow, words can really be arranged in any order! But hang in there, we'll break this down:
Gradient boosting classifiers are a group of machine learning algorithms that combine many weak learning models together to create a strong predictive model. Decision trees are usually used when doing gradient boosting. Gradient boosting models are becoming popular because of their effectiveness at classifying complex datasets, and have recently
Generative models are a family of AI architectures whose aim is to create data samples from scratch. They achieve this by capturing the data distributions of the type of things we want to generate.
These kind of models are being heavily researched, and there is a huge amount of
Are you interested in using a neural network to generate text? TensorFlow and Keras can be used for some amazing applications of natural language processing techniques, including the generation of text.
In this tutorial, we'll cover the theory behind text generation using a Recurrent Neural Networks, specifically a Long
